Field of the Invention
The present invention is generally directed to financial-bio-psycho social management models for optimal treatment of medical conditions. More particularly, the present invention discloses a system, process and, in particular, an improved algorithmic based non-transitory computer writeable medium for treatment of medical conditions in a cost effective fashion.
The system, process and associated algorithmic medium further includes a related module for optimizing the diagnosis, treatment and resolution of worker injury events, such as associated with a workman compensation claim, and which improves upon the existing paper based module by synthesizing, in a digital environment, symptom, treatment and progress variables in a multi-party available format. In particular, the injury event module greatly increases care provider (physician) efficiency by integrating and compiling electronically, in easily readable and time elapsed formats, symptom and treatment variables. The module additionally provides a reasonable and agreeable model, such as between the employer/payer and worker, for establishing minimal goals for facilitating return to work.
A further related rehabilitation module, such as not limited to a worker injury event but also including any injury event associated with a typical accountable care organization (insurer/other payor/etc.) in a general health application is provided for establishing and tracking a patient's functional independent (FEM) measurement score. As with the workman compensation module, the rehabilitation module integrates the establishment of current conditions, achievable goals, and time based tracking of the patient treatment (including time elapsed changes in response to flat line response indicating a non-effective treatment plan) in order to define a patient goal outcome and to optimize real time treatment and progress tracking to that goal.
In this fashion, the time frame between a worker injury event (or rehab setting reported event) and an eventual agreed to return to work event (or final rehab setting event) is minimized through the maximization of effectiveness of the treatment protocols, as well as the maximization of the efficiency of the care provider by synthesizing into a simplified and time interval dynamic record the critical variables associated with the treatment of the patient as derived from the best practices and critical pathway modules and as integrated into these specific applications.
Description of the Background Art
The prior art is documented with examples of systems and methods, such as utilized in the medical field. A first example of this is set forth in Moore, U.S. Pat. No. 7,693,727 which teaches interactive systems and methods for directing, integrating, documenting, and tracking steps taken by medical providers during the process of care for a patient's given condition. Doctors' actions are directed by a prescriptive protocol—a checklist of discrete steps designed for efficient or optimal care of an individual patient's specific condition. The step-by-step checklist is abstracted from decision tree guidelines for the optimal work up and treatment for the condition using probability-based methodology. The care protocols can be derived from widely available and non-proprietary guidelines and decision trees based on public medical research literature.
In one embodiment, the invention can be employed by a primary care clinician at the point of referral into the specialist sector, and at the specialist level when proposing a risky or expensive or otherwise problematic medical or surgical diagnostic or treatment intervention. At these two critical transaction points in care, the checklist functions like a lock, based on a hidden clinical decision algorithm (an explanation of which can be displayed upon request). The system asks the clinician for data and then generates the patient's optimal checklist, displaying it as a point and click form keyed to the stage of care being undertaken by each doctor. As the clinician enters data into the checklist, a decision engine determines whether the checklist data satisfies predetermined criteria for authorization of the proposed action. The system can also document each transaction taken in the process of care to create an electronic record that can be made accessible to all clinicians involved in the process of care.
Moore, US 2004/0044546 teaches interactive methods and systems for directing, integrating, documenting and tracking steps taken by medical providers during the process of care for a given patient's condition. Doctors' actions are directed by a prescriptive protocol—a checklist of discrete steps designed for efficient or optimal care of an individual patient's specific condition. The step-by-step checklist is abstracted from decision tree guidelines for the optimal work up and treatment for the condition using probability-based methodology. The care protocols can be derived from widely available and non-proprietary guidelines and decision trees based on public medical research literature.
In one embodiment, the invention can be employed by a primary care clinician at the point of referral into the specialist sector, and at the specialist level when proposing a risky or expensive or otherwise problematic medical or surgical diagnostic or treatment intervention. At these two critical transaction points in care, the checklist functions like a lock, based on a hidden clinical decision algorithm (an explanation of which can be displayed upon request). The system asks the clinician for data and then generates the patient's optimal checklist, displaying it as a point and click form keyed to the stage of care being undertaken by each doctor. As the clinician enters data into the checklist, a decision engine determines whether the checklist data satisfies predetermined criteria for authorization of the proposed action. The system can also document each transaction taken in the process of care to create an electronic record that can be made accessible to all clinicians involved in the process of care.
A further example of the prior art is the healthcare providing organization (HPO) model of Cusimano-Reaston et al., U.S. Pat. No. 8,117,047, and which teaches a preferred provider network (PPO) or other membership agreement that allows individuals or groups to join via a membership contract. The contract allows the HPO to provide a technical component of a medical evaluation or service. Additionally, the HPO employs or retains the services of healthcare professionals who participate in and monitor an evaluation of a patient who can be at a remote location from the healthcare professional. The HPO provides a medical diagnostic unit, which is known as an EFA-2, that allows the healthcare professional to receive data that pertains to the patient via a real-time communication protocol, or the patient data is collected and stored on an electronic storage device. The healthcare professional then analyzes the patient data and issues recommended treatment.
Lee, US 2012/0109689 teaches a support system for improved quality healthcare, defined as MEGICS (Medical+Logistics), developed in order to improve quality of care and enhance the efficiency of operation of healthcare facilities and providers. When front-line healthcare doctors and nurses make various clinical decisions, MEGICS management system provides them with relevant clinical knowledge in a timely manner with the stated objective being to increase user satisfaction and provide better quality of healthcare services.
Gliklich, U.S. Pat. No. 8,489,412, teaches a data processing system for determining clinical outcomes of medical data gathered by the system. A doctor defines a medical study and can administer and collect data relevant to that study in real time from potentially geographically diverse doctors, patients and other people associated with the study. The system can analyze the medical data in real-time according to any number of clinical algorithms that may be custom defined and edited before and during the study. The clinical algorithms produce clinical outcome data that can be used for treatment of patients participating in the study immediately after the data is input and analyzed. The medical outcomes can indicate such things as performance comparisons, composite outcomes, and risk stratification and assessments for such things as treatments, drugs, illnesses, doctors, patients and physicians groups.
McIlroy, U.S. Pat. No. 5,583,758, teaches a health care management system for use by hospitals, physicians, insurance companies, health maintenance organizations, and others in the health care field includes a processing unit and health condition guidelines. A user inputs information related to the health condition of an individual and guideline treatment options are identified. The user also inputs actual or proposed and final recommendation treatments for the same individual. The resulting comparative information can be used to modify the actual or proposed treatment, or provide explanatory information as to reasons for the difference between the final recommendation treatment and guideline treatment options. Also, the comparative information can be used by a reviewer for evaluation or utilization purposes.
Goetzke, US 2003/0097185, discloses a medical resource for chronic pain patients forecasted using a method or computer software product to improve accuracy in forecasting medical resources, decrease the time required to forecast medical resources, and many other benefits. Desired patient indicia including direct medical indicia, indirect medical indicia, and non-medical indicia are selected to serve as independent variables. At least one chronic pain indication is selected to serve as a dependent variable. A chronic pain forecasting model is created using the patient indicia and the chronic pain indication. The chronic pain forecasting model is applied to a chronic pain patient indicia to create a patient forecast. Many different embodiments of the chronic pain patient dynamic medical resources forecaster method and software product are possible.
In summary, and while describing various systems, methods and protocols for attempting to optimize the efficiency of patient care, the prior art as a generalization acknowledges the inviolability of the present healthcare delivery model with its existing compensation and incentive structures. These notably reward physicians and other medical providers based on the quantum of care provided (e.g. tests conducted, surgical procedures performed, etc.) and as opposed to tying such compensation/incentives to documentable patient outcomes.